{"id":"W4407689898","doi":"10.1038/s41467-025-56893-9","title":"Virtual fragment screening for DNA repair inhibitors in vast chemical space","year":2025,"lang":"en","type":"article","venue":"Nature Communications","topic":"Cancer therapeutics and mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Science for Life Laboratory; Uppsala Universitet; Vetenskapsrådet; Kungliga Tekniska Högskolan; Knut och Alice Wallenbergs Stiftelse; European Commission; Cancerfonden; European Federation of Pharmaceutical Industries and Associations; Diamond Light Source; McGill University","keywords":"Chemical space; Virtual screening; Drug discovery; Fragment (logic); Computational biology; DOCK; Chemical library; Small molecule; Docking (animal); Combinatorial chemistry; Computer science; DNA; Chemistry; Biology; Bioinformatics; Biochemistry; Algorithm; Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001650982,0.00008963476,0.00009189901,0.00005533753,0.0000904661,0.00001276027,0.0003973558,0.000274965,0.000001963456],"category_scores_gemma":[0.00006974474,0.0000955971,0.0001000913,0.0001436485,0.00004683331,0.00000210711,0.0002930464,0.0002776862,5.325842e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003240438,"about_ca_system_score_gemma":0.00007393787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009001247,"about_ca_topic_score_gemma":0.0002491213,"domain_scores_codex":[0.9994395,0.00003044224,0.0001471963,0.0001903074,0.00005581562,0.0001367689],"domain_scores_gemma":[0.9989451,0.00004022494,0.00003800769,0.0008760892,0.0000718685,0.00002876588],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009352387,0.0001670839,0.000538959,0.00001127934,0.00009363847,1.762973e-7,0.00007557272,0.00002758698,0.9283799,0.05012103,0.009924174,0.01056708],"study_design_scores_gemma":[0.0006547111,0.00006415437,0.0002980855,0.00004691453,0.00002177332,8.144103e-7,0.000151875,0.0005160422,0.3532619,0.0004174548,0.6444367,0.0001295964],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.761639,0.07290305,0.09230583,0.0498434,0.002342979,0.003986313,0.0003539506,0.0002928317,0.01633267],"genre_scores_gemma":[0.98308,0.0004267831,0.014443,0.001130365,0.00007086072,0.0001391269,0.0002179798,0.00001206013,0.0004798217],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6345125,"threshold_uncertainty_score":0.3898337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01440605193206448,"score_gpt":0.3088082304449167,"score_spread":0.2944021785128522,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}